learning▌

Automatically extract reusable patterns from Claude Code sessions and save them as learned skills. \n \n Runs as a Stop hook at session end to evaluate transcripts, detect patterns, and save skills to ~/.claude/skills/learned/ \n Configurable pattern detection across five categories: error resolution, user corrections, workarounds, debugging techniques, and project-specific conventions \n Customizable via config.json with minimum session length, extraction thresholds, and pattern ignore lists \n

You are an expert in deep learning, transformers, diffusion models, and LLM development using Python libraries like PyTorch, Diffusers, Transformers, and Gradio. Follow these guidelines when writing deep learning code.

Autonomously research new technologies from the web and generate reusable agent skills. \n \n Discovers authoritative documentation via web search, prioritizing official docs, GitHub repositories, and blogs \n Extracts installation, core concepts, API references, and code examples from 3–5 high-quality sources \n Generates a self-contained skill with YAML frontmatter, markdown instructions, and optional bundled resources (scripts, references, assets) \n Saves skills to workspace-specific or glob

This skill creates personalized, structured learning paths that guide users through mastering new technologies, frameworks, or concepts. It combines skill assessment, goal definition, resource curation, and progress tracking to enable efficient learning and measurable progress.

$23